{"id":"W4392000825","doi":"10.1007/s10230-024-00970-w","title":"Analysis of Uncertainty and Sensitivity in Tailings Dam Breach-Runout Numerical Modelling","year":2024,"lang":"en","type":"article","venue":"Mine Water and the Environment","topic":"Tailings Management and Properties","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Precision Nanosystems (Canada); Queen's University; Klohn Crippen Berger (Canada); University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Suncor Energy Incorporated","keywords":"Tailings; Sensitivity (control systems); Flow (mathematics); Tailings dam; Hydrogeology; Geology; Moment (physics); Mining engineering; Geotechnical engineering; Probabilistic logic; Environmental science; Engineering; Mechanics; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004299741,0.0008719895,0.0008343529,0.001651762,0.000558992,0.001390743,0.0009940123,0.001304669,0.0006137438],"category_scores_gemma":[0.015371,0.0005592843,0.001300288,0.0009220128,0.0007453287,0.001188792,0.001168221,0.001195605,0.00005432681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001385022,"about_ca_system_score_gemma":0.0008711453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01617234,"about_ca_topic_score_gemma":0.006693206,"domain_scores_codex":[0.9984432,0.0006815972,0.000123775,0.0002219541,0.0003769648,0.0001525086],"domain_scores_gemma":[0.9878967,0.009813605,0.0008708155,0.0005077771,0.0007888477,0.0001224061],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001458289,0.00001115722,0.002929973,0.00001351244,0.00002430326,0.00003554184,0.0000218214,0.9948015,0.000370164,0.0006692782,0.00002898382,0.001079165],"study_design_scores_gemma":[0.000001544968,0.00001403264,0.00116654,0.000006150005,0.000007065858,0.00000920951,0.00001571539,0.9977767,0.0004336012,0.0004864595,0.00007364261,0.00000934048],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8801306,0.0003051582,0.1147384,0.0003375592,0.00003270922,0.0001028338,0.0006945335,0.0002469984,0.003411138],"genre_scores_gemma":[0.9934973,0.00005987061,0.006055891,0.00001457679,0.000005584646,0.00002914979,0.0001596102,0.000013424,0.0001645788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01617234,"threshold_uncertainty_score":0.03215641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007132151849681787,"score_gpt":0.1686210420244061,"score_spread":0.1614888901747243,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}